The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39958-9_24. Abstract. Application development for modern high-performance systems with Graphics Processing Units (GPUs) currently relies on low-level programming approaches like CUDA and OpenCL, which leads to complex, lengthy and error-prone programs. In this paper, we present SkelCL – a high-level programmi...

Heterogeneous systems are becoming increasingly common. Relatedly, the popularity of OpenCL is growing, as it provides a unified mean to program a wide variety of devices including GPUs or multicore CPUs. More recently, the Heterogeneous Programming Library (HPL) targets the same variety of systems as OpenCL, intending to improve their programmability. The main drawback of such unified approach...

Heterogeneous computing systems can dramatically increase the performance of parallel applications on clusters. Currently, most applications that utilize OpenCL devices (CPUs, GPUs, Accelerators), run their device-specific code only on devices of the same computer were the application runs. This paper presents the VirtualCL (VCL) cluster platform, a wrapper for OpenCL that allows most unmodifie...

High-performance computing systems today include a variety of compute devices such as multi-core CPUs, GPUs and many-core accelerators. OpenCL allows programming different types of compute devices using a single API and kernel language. However, there is no standard matrix operations library in OpenCL for operations such as matrix multiplication that works well on a variety of hardware from mul...

This work presents an effort to bridge the gap between abstract high level programming and OpenCL by extending an existing high level Java programming framework (APARAPI), based on OpenCL, so that it can be used to program FPGAs at a high level of abstraction and increased ease of programmability. We run several real world algorithms to assess the performance of the framework on both a low end ...

OpenCL (Open Computing Language) is a heterogeneous programming framework for developing applications that executes across a range of device types made by different vendors[11] which efficiently maps to both heterogeneous and homogeneous, single or multiple device system consisting of CPUs, GPUs and others types of devices. OpenCL provides many benefits in the field of high-performance computin...

of the Dissertation Cross-Platform Heterogeneous Runtime Environment by Enqiang Sun Doctor of Philosophy in Computer Engineering Northeastern University, April 2016 Dr. David Kaeli, Adviser Heterogeneous platforms are becoming widely adopted thanks to the support from new programming languages and models. Among these languages/models, OpenCL is an industry standard for parallel programming on h...

Рассматриваются программы, выполняемые на видеокартах общего назначения и представленные в виде “ядер”, не содержащих циклов с неопределенной продолжительностью. Такие ядра могут быть реализованы, например, помощью технологий CUDA или OpenCL. Для оценки времени работы подобных программ предложены модели их работы: от совсем “наивной” до более реалистичных. Все они формулируются как матричные вы...

This paper presents an accelerated approach for training logistic regression in parallel and running on Graphics Processing Units (GPU). Many prediction applications employed logistic regression for building an accomplished prediction model. This process requires a long time of training and building an accurate prediction model. Many scientists have worked out in boosting performance of logisti...